An increasing number of planners can handle uncertainty in
the domain or in action outcomes. However, less work has addressed
building plans when the planner’s world can change independently of
the planning agent in an uncertain manner. In this paper, I model this
change with external events that concisely represent some aspects of
structure in the planner’s domain. This event model is given a formal
semantics in terms of a Markov chain, but probabilistic computations
from this chain would be intractable in real-world domains. I describe
a technique, based on a reachability analysis of a graph built from
the events, that allows abstractions of the Markov chain to be built
to answer specific queries efficiently. I prove that the technique is
correct. I have implemented a planner that uses this technique, and I
show an example from a large planning domain.

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